Skip to main content
Log in

An alternative approach to robust collocation

  • Published:
Bulletin Géodésique Aims and scope Submit manuscript

Abstract

The now classical collocation method in geodesy has been derived byH. Moritz (1970; 1973) within an appropriate Mixed Linear Model. According toB. Schaffrin (1985; 1986) even a generalized form of the collocation solution can be proved to represent a combined estimation/prediction procedure of typeBLUUE (Best Linear Uniformly Unbiased Estimation) for the fixed parameters, and of type inhomBLIP (Best inhomogeneously LInear Prediction) for the random effects with not necessarily zero expectation. Moreover, “robust collocation” has been introduced by means of homBLUP (Best homogeneously Linear weakly Unbiased Prediction) for the random effects together with a suitableLUUE for the fixed parameters. Here we present anequivalence theorem which states that the robust collocation solution in theoriginal Mixed Linear Model can identically be derived as traditionalLESS (LEast Squares Solution) in amodified Mixed Linear Model without using artifacts like “pseudo-observations”. This allows us a nice interpretation of “robust collocation” as an adjustment technique in the presence of “weak prior information”.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • A. BJERHAMMAR: Theory of Errors and Generalized Matrix Inverses. Elsevier: Amsterdam, etc. 1973.

    Google Scholar 

  • A. DERMANIS: Geodetic applications of interpolation and prediction. Eratosthenes22 (1988), pp. 229–262.

    Google Scholar 

  • D. HARVILLE: Extension of the Gauss-Markov theorem to include the estimation of random effects. Ann. Statist.4 (1976), pp. 384–395.

    Article  Google Scholar 

  • K.R. KOCH: Parameter Estimation and Hypothesis Tests in Linear Models. Springer: Berlin, etc. 1988.

    Book  Google Scholar 

  • E.J. KRAKIWSKY: The method of least squares: A synthesis of advances. Dept. of Surveying Eng., The University of Calgary, Publ. No.10003, Calgary/Alberta 1989 (last reprint).

  • H. LÄUTER: Optimale Vorhersage und Schätzung in regulären und singulären Regressionsmodellen, Math. OF Statist.1 (1970), pp. 229–243.

    Google Scholar 

  • B. MIDDEL and B. SCHAFFRIN: Stabilized determination of geopotential coefficients by the mixed hom BLUP approach,in: R. Rapp (ed.), Progress in the Determination of the Earth's Gravity Field, Dept. of Geodetic Sci. & Surveying, The Ohio State University, Report No.397, Columbus/Ohio 1989, pp. 27–30.

  • H. MORITZ: A generalized least-squares model. Studia Geophys. et Geodaet.14 (1970), pp. 353–362.

    Article  Google Scholar 

  • H. MORITZ: Least-squares collocation. Deutsche Geodät. Kommission A-75, Munich 1973.

  • B. SCHAFFRIN: Model choice and adjustment techniques in the presence of prior information. Dept. of Geodetic Sci. & Surveying, The Ohio State University, Report No.351, Columbus/Ohio 1983.

  • B. SCHAFFRIN: A note on linear prediction within a Gauss-Markov model linearized with respect to a random approximation;in: T. Pukkila/S. Puntanen (eds.), Proc. of the First Tampere Seminar on Linear Models (1983), Dept. of Math. Sci./Statistics, Univ. of Tampere/Finland, Report No. A-138 (1985), pp. 285–300.

  • B. SCHAFFRIN: Das geodätische Datum mit stochastischer Vorinformation. Deutsche Geodät. Kommission C-313, Munich 1985.

  • B. SCHAFFRIN: On robust collocation;in: F. Sansò (ed.), Proc. of the First Hotine-Marussi Symp. on Math. Geodesy (Rome 1985), Milano 1986, pp. 343–361.

  • B. SCHAFFRIN: Less sensitive tests by introducing stochastic linear hypotheses;in: T. Pukkila/S. Puntanen (eds.), Proc. of the Second Int. Tampere Conf. on Statistics, Dept. of Math. Sci./Statistics, Univ. of Tampere/Finland, Report No. A-184 (1987), pp. 647–664.

  • B. SCHAFFRIN: Tests for random effects based on homogeneously linear predictors. Paper presented at the Workshop on “Theory and Practice in Data Analysis”, Berlin (East), August 1988.

  • S.R. SEARLE: Prediction, mixed models, and variance components;in: F. Proschan/R.J. Serfling (eds.), Reliability and Biometry, SIAM: Philadelphia 1974, pp. 229–266.

    Google Scholar 

  • R.A. SNAY: Enhancing the spatial resolution of fault slip by introducing prior information. Manus. Geodaet. (submitted March 1989).

  • H. THEIL and A.S. GOLDBERGER: On pure and mixed statistical estimation in economics. Int. Econ. Rev.2 (1961), pp. 65–78.

    Article  Google Scholar 

  • H. TOUTENBURG: Probleme linearer Vorhersagen im allgemeinen linearen Regressionsmodell. Biometr. Z.12 (1970), pp. 242–252.

    Article  Google Scholar 

  • H. WOLF: Über verallgemeinerte Kollokation. Z. für Vermessungswesen99 (1974), pp. 475–478.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schaffrin, B. An alternative approach to robust collocation. Bull. Geodesique 63, 395–404 (1989). https://doi.org/10.1007/BF02519637

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02519637

Keywords

Navigation